prompt template from string

docs/modules/prompts/examples/prompt_management.ipynb

@@ -151,6 +151,47 @@
     "multiple_input_prompt.format(adjective=\"funny\", content=\"chickens\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "72f32ff2",
+   "metadata": {},
+   "source": [
+    "## From Template\n",
+    "You can also easily load a prompt template by just specifying the template, and not worrying about the input variables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "2a81f2f8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "template = \"Tell me a {adjective} joke about {content}.\"\n",
+    "multiple_input_prompt = PromptTemplate.from_template(template)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d365b144",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "PromptTemplate(input_variables=['adjective', 'content'], output_parser=None, template='Tell me a {adjective} joke about {content}.', template_format='f-string', validate_template=True)"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "multiple_input_prompt"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b2dd6154",

langchain/chains/llm.py

@@ -1,5 +1,4 @@
 """Chain that just formats a prompt and calls an LLM."""
-from string import Formatter
 from typing import Any, Dict, List, Sequence, Union
 
 from pydantic import BaseModel, Extra
@@ -132,10 +131,5 @@ def _chain_type(self) -> str:
     @classmethod
     def from_string(cls, llm: BaseLLM, template: str) -> Chain:
         """Create LLMChain from LLM and template."""
-        input_variables = {
-            v for _, v, _, _ in Formatter().parse(template) if v is not None
-        }
-        prompt_template = PromptTemplate(
-            input_variables=list(input_variables), template=template
-        )
+        prompt_template = PromptTemplate.from_template(template)
         return cls(llm=llm, prompt=prompt_template)

langchain/prompts/prompt.py

@@ -1,6 +1,7 @@
 """Prompt schema definition."""
 from __future__ import annotations
 
+from string import Formatter
 from typing import Any, Dict, List
 
 from pydantic import BaseModel, Extra, root_validator
@@ -117,6 +118,14 @@ def from_file(
             template = f.read()
         return cls(input_variables=input_variables, template=template)
 
+    @classmethod
+    def from_template(cls, template: str) -> PromptTemplate:
+        """Load a prompt template from a template."""
+        input_variables = {
+            v for _, v, _, _ in Formatter().parse(template) if v is not None
+        }
+        return cls(input_variables=list(input_variables), template=template)
+
 
 # For backwards compatibility.
 Prompt = PromptTemplate

tests/unit_tests/prompts/test_prompt.py

@@ -13,6 +13,27 @@ def test_prompt_valid() -> None:
     assert prompt.input_variables == input_variables
 
 
+def test_prompt_from_template() -> None:
+    """Test prompts can be constructed from a template."""
+    # Single input variable.
+    template = "This is a {foo} test."
+    prompt = PromptTemplate.from_template(template)
+    expected_prompt = PromptTemplate(template=template, input_variables=["foo"])
+    assert prompt == expected_prompt
+
+    # Multiple input variables.
+    template = "This {bar} is a {foo} test."
+    prompt = PromptTemplate.from_template(template)
+    expected_prompt = PromptTemplate(template=template, input_variables=["bar", "foo"])
+    assert prompt == expected_prompt
+
+    # Multiple input variables with repeats.
+    template = "This {bar} is a {foo} test {foo}."
+    prompt = PromptTemplate.from_template(template)
+    expected_prompt = PromptTemplate(template=template, input_variables=["bar", "foo"])
+    assert prompt == expected_prompt
+
+
 def test_prompt_missing_input_variables() -> None:
     """Test error is raised when input variables are not provided."""
     template = "This is a {foo} test."